FE595 Financial Technology (FinTech)

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Course Catalog Description

Introduction

This course deals with networking technology underlying activities of markets, institutions and

participants. The overall purpose is to give students the knowledge to build and maintain cloud applications in secure and extendable ways. The course will also introduce the theory behind state-of-the-art tools like block-chain and deep learning with neural networks.

Campus Fall Spring Summer
On Campus X
Web Campus X

Instructors

Professor Email Office
Kenneth Blaney
kblaney@stevens.edu TBA



More Information

Course Description

Video lectures will be posted once per week on Tuesday evenings/Wednesday mornings EST. Lectures will introduce

the concepts behind proper design and management of a cloud based service along with demonstrations of examples. Virtual office hours will be hosted Thursday evening or upon request to answer questions that arise from the previous video lectures. Emails and posts from students are encouraged and will be answered as soon as possible.







Grading

Grading Policies

The final grade in the class will be determined in the following manner:

  • 30% Homeworks
  • 35% Midterm
  • 35% Final Exam

Assessments will be conducted through individual or group assignments. Source code should be put into a .zip file and emailed or made available on GitHub as required. Python projects should comply with PEP8 standards and be well documented where possible. Projects involving web services should be hosted online and be available at the submission deadline.

The intent of this structure is to mimic the basic structure one might encounter in industry where code bases will often be transferred from person to person as staff changes over time. As a result, there will be a focus on writing code that can be understood and maintained.


Lecture Outline

Topic Reading
Week 1 Python Review • Set up a Python3.6 development environment.

• Understand the structure of an OOP Python project. • Learn about git. • Brief discussion about common libraries including numpy

Week 2 Flask • Understand how to create a RESTful API in Python.

• Become familiar with cURL calls and understand their proper usage. • Be comfortable using the Postman tool

Week 3 Amazon Web Services • Learn to host a Flask App on a Virtual Machine.

• Extend the above with nginx and related services.

Week 4 Amazon Web Services - Lambda • Learn what Lambda is and why we’d want to use it.

• Learn to host a service using Lambda.

Week 5 Databases and Storage • Learn about storing and recovering data using Redis and SQL.
Week 6 Review and assignment of midterm projects • Review of tools and a discussion of projects.

• Discuss methods of project management.

Week 7 Monday Schedule. No class.
Week 8 Project Presentation • Be able to explain the purpose of your project and the methods used to make it possible.
Week 9 ZMQ • Understand the usage of pyZMQ.

• Be able to explain the difference between ZMQ and cURL.

Week 10 The Theory of Neural Networks • Understand what a dense neural network is and how training works.

• Be able to explain the uses and limitations of a neural network.

Week 11 Introduction to Tensor Flow • Become familiar with Tensor Flow to implement dense and convolutional layers in a neural network.

• Be conversant in the structure of neural networks to be able to learn additional libraries/capabilities as needed. • Learn to import

Week 12 The Theory of Blockchain • Understand the basic problem blockchain was invented to solve.

• Be able to explain how a 51% attack works.

Week 13 Git and Cryptocurrencies • Be able to explain how Git like version management systems work.

• Compare and contrast cryptocurrencies with other financial instruments. • Understand the concept of a Smart Contract on the Etherium network.

Week 14 Review and assignment of final projects • Review of tools and a discussion of projects.